Companies hiring for AI search optimization are writing job descriptions that describe technical SEO work, says AI search visibility consultant Cassie Clark. Technical SEO determines whether a page can be found. It doesn’t determine whether an AI model treats the brand as the right answer.
— Abingdon, Va., July 29, 2026 — Companies hiring for AI search optimization are writing job descriptions that describe technical SEO work, according to AI search visibility consultant Cassie Clark, host of the Found in AI podcast. Clark argues the scope is incomplete and leaves the larger problem unowned.
Technical search work determines whether a page can be found and parsed. It does not determine whether a large language model treats a brand as the right answer to a question. That decision is driven by the language on the page — the category a brand claims, the words it uses to describe what it does, and whether those words stay consistent everywhere the brand appears.
The consistency problem is where most organizations lose ground. When demand generation, partner marketing, sales, and PR each adapt the core message for their own audience, the cumulative drift can move a brand into a different semantic category without anyone deciding to. Language models read that inconsistency as a lack of corroboration, and corroboration is a significant input into which brands they cite. Clark has written separately on what to look for when evaluating AI search expertise, arguing that most hiring criteria in the category test for the wrong skills.
“An SEO background isn’t the wrong background. It’s an incomplete one,” said Clark, AI search visibility consultant and host of Found in AI. “If nobody owns whether the company describes itself the same way in every place it appears, that’s not an SEO gap. That’s a leadership gap.”
The point was developed in a recent episode featuring David Kirkdorffer, a fractional marketer who has worked in B2B marketing since the 1990s and advises CMOs, CROs and CEOs on brand discoverability in large language models. Kirkdorffer describes the distinction using a library analogy: “SEO can help you be found on the shelf, but it doesn’t help get you mentioned or cited.” He argues product marketing functions as the hub that supplies consistent messaging to every other team, making it the group with the greatest influence over AI visibility outcomes.
Both point to the same conclusion for marketing leaders: AI search visibility is a cross-functional responsibility rather than a specialist assignment, and organizations that scope it as a single technical hire tend to leave the determining factors unassigned.
Clark’s full breakdown of which teams actually own AI search visibility is available on her site, along with details of the AI Search Visibility Audit she runs for enterprise and scaling brands. The complete episode is available on Found in AI.
ABOUT CASSIE CLARK
Cassie Clark is an AI search visibility consultant who helps enterprise and scaling brands appear in AI-generated answers. She created the FSA Framework (Freshness, Structure, Authority), published by HubSpot, and hosts Found in AI, a twice-weekly podcast on AI search, GEO, and AEO. She writes The Visibility Report and contributes to HubSpot and EIN Presswire, among other publications.
Contact Info:
Name: Cassie Clark
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Organization: Cassie Clark Marketing
Address: 17525 Ridgeview Dr, Abingdon, VA 24211
Website: https://cassieclarkmarketing.com
Release ID: 89199249
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